Oklahoma
20.8 13.5 10.7 14.5 19.1 18.8 29.0 19.2 20.6 18.2 17.9 25.6 25.9 31.9 20.2
1.11 1.23 0.96 0.37 1.39 1.84 0.81 3.17 3.58 1.24 1.04 1.54 1.13 2.77 1.27
0.58, 2.12 0.49, 3.12 0.32, 2.92 0.16, 0.87 0.72, 2.68 0.84, 4.01 0.43, 1.55 1.27, 7.88 1.43, 8.95 0.55, 2.80 0.44, 2.45 0.70, 3.39 0.57, 2.22 1.52, 5.07 0.60, 2.65
408 372 375 324 425 381 411 370 457 418 356 390 391 409 415
Oregon
Pennsylvania
Rhode Island*
South Carolina
South Dakota
Tennessee
Texas*
Utah*
Virginia
Vermont
Washington
Wisconsin
West Virginia*
Wyoming
Abbreviations: CI=confidence interval; N =study population size; n =sample size; aOR=adjusted odds ratios.
a “Percent” refers to the population-weighted estimate. *One-sided P value <0.05 using Wald Chi-square tests. b Models adjusted for age, insurance, race, special healthcare need, and family structure.
region of residence). The PDS prevalence varied by state, and covariate-adjusted logit models indicate significant variation (Table 3); we therefore proceeded with MLMs. AdjustedMLMs indicate the random intercept and random slope model fit best (Table 4); subsequently, both the PDS and the MH-PDS association varied by state. Based on this model, children whose care meets MH criteria have 1.24 greater odds of having received a PDS compared to those without MH care (adjusted OR: 1.24; 1.10, 1.38). The percent of variability in the PDS prevalence between states is 4% (ICC = 0.04). DISCUSSION Population Distribution Implications This is the first study to date that has examined the MH-PDS association accounting for the influence of a child’s resident state. Our work indicates that a nominal fraction of US children have received a PDS in the 12 months prior to the survey. Greater than 80%, or about 15.9million out of the total 19.9millionUS children between 10months and 5 years of age, did not meet PDS criteria. Given the reliability of the survey, we presume a substantial number of young children at risk for DD have missed an important opportunity for early intervention. Looking ahead, the marginal PDS rate may forecast changes in the distribution of adult disability indicators over the next few decades. Between 2005 and 2010, there was an increase of 2.2 million disabled US adults,
despite a steady disability rate (18.7%). 13 The increase may reflect CSHCNwho are reaching adulthood due to medical advances over the past 30 years. 14 Despite the improvements in life expectancy and chronic disease management, adults with disabilities face disproportional social challenges. The 2010 census showed 20% of severely disabled adults were employed in the 24 months prior to the survey versus 54.8% (non-severe) and 61.1% (not disabled). 13 Also, persistent poverty (24 months) was experienced differentially: 11% of severely disabled, 4.9% of non-severe, and 3.8% of non- disabled. 13 Perhaps by considering the lack of PDS as a proxy for delayedDDdiagnosis rather than an indicator of services provided, the urgency for understanding the mechanisms for why children are not receiving necessary screenings may be greater. Indeed, from this perspective, research is not constrained to defend the need for increased PDS to inform health policy but only to highlight a connection: the rate of adult disability is constant, and this parallels the rate for delayed DD diagnosis (PDS) and subsequent acquisition of early intervention services.
State and Federal Health Policy Implications - Health Insurance Disparities
We found PDS odds were higher in children with an MH than without. This was expected given the AAP policy outlines a fundamental service for an MH provider is to conduct a PDS. We found theMH-PDS association remained after accounting for identified confounders. Among these
J La State Med Soc VOL 166 May/June 2014 115
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